Prostate cancer (PCa) is the most common solid organ malignancy affecting American men and the second leading cause of cancer related death. Approximately one million prostate biopsies are performed yearly in the U.S. The vast majority of these biopsies are performed due to elevated levels of the PCa marker prostate-specific antigen (PSA). However, only a quarter of these biopsies result in a diagnosis of PCa, highlighting the inadequate performance of currently available parameters such as PSA to predict PCa. Persistently elevated PSA levels and/or other clinical parameters that prompted initial biopsies contribute to stress and anxiety among both patients and their urologists. Thus, the predictive performance of currently available clinical parameters such as PSA is limited. Furthermore, management of men following negative prostate biopsy for prostate cancer is challenging. Novel biomarkers are urgently needed to better determine the need for initial and repeat prostate biopsy and assess an individual's risk.
Single nucleotide polymorphisms (SNPs) are stable genetic markers throughout the human genome, which can be tested for their association with various disease traits. These markers can be tested at birth and will not change in a patient's lifetime and thus represent a new form of biomarkers that predict lifetime risk to disease as opposed to an immediate risk.
Numerous PCa risk-associated single nucleotide polymorphisms (SNPs) have been discovered from genome-wide association studies (GWAS). To date, 33 SNPs have been consistently found, in several populations of Caucasian race, to be associated with prostate cancer (PCa) risk (Table 1). These risk-associated SNPs have been consistently replicated in multiple case-control study populations of European descent. Although each of these SNPs is only moderately associated with PCa risk, a genetic score based on a combination of risk-associated SNPs can be used to identify an individual's risk for PCa. These risk-associated SNPs have broad practical applications because they are common in the general population.
The present invention overcomes previous shortcomings in the art by identifying significant statistical associations between multiple genetic markers and prostate cancer risk.